This is a tutorial on how to map spatial data with R. In this
tutorial, census data will be obtained using two different methods and
then mapped to show the housing density in Travis County - Texas,
emphasizing Downtown Austin in the years 1990 and 2000. This tutorial is
in two parts. In part one, census data will be downloaded from the NHGIS website and then mapped. The
second part of this tutorial follows an easier method of census data
extraction using the tidycensus package
and how to map the obtained data. The Census Geography used in this
tutorial is Block Groups.
Objectives
This tutorial assumes that the learner is familiar with or has basic knowledge of Geographic Information Systems. Now let’s begin! :)
The first step to mapping the census data obtained from the NHGIS
website is to look at the dataset and then process it for mapping. This
section aims to import the downloaded dataset into R and make them clean
enough for mapping. The dplyr tool is required to help with
easy data manipulation. This function forms part of the tidyverse package,
thus, while it can be installed and opened individually, installing and
opening the full tidyverse is ideal for this tutorial. The
sf package is
useful for handling spatial vector data and it will be useful in this
tutorial. This tutorial assumes that all the required packages have
already been installed in R. If any package has not been installed, use
the install.packages() function to install it.